1,614 responses from 269 respondents to 6 items.
One of 4 tables from the same source; this one is the risky_driving table. The others are listed under Related tables.
| Description | Frequency of six risky driving behaviours (running red lights, tailgating, speeding, illegal overtaking, no seatbelt, drunk driving; 1-5), from 269 young Chinese drivers |
|---|---|
| Reference | Li, W., Liu, J., Wang, Y., & Sun, L. (2025). Psychometric adaptation and validity of the Resistance to Peer Influence Scale among young Chinese drivers and its links with peer pressure and risky driving behaviours. Behavioral Sciences, 15(9), 1237. |
| DOI | 10.3390/bs15091237 |
| Licence | CC BY 4.0 |
| Source data | https://doi.org/10.6084/m9.figshare.29815862 |
| Responses | 1,614 |
|---|---|
| Respondents | 269 |
| Items | 6 |
| Response categories | 5 |
| Responses per respondent | 6 |
| Responses per item | 269 |
| Density | 1 |
| Longitudinal | FALSE |
| sample | General/non-specific |
|---|---|
| measurement tool | Survey/questionnaire |
| item format | Likert Scale/selected response |
| primary language(s) | chi |
This codebook is reconstructed by the IRW from the IRW data standard and the script that built it, li_2025_peer_driving.py. It is our best reading, not the source’s own codebook, and it may contain mistakes. Where the two disagree, the source data are the authority. If you find an error, please tell us.
| Column | What it is | Source column |
|---|---|---|
| IRW standard columns | ||
id | IRW standard Identifier for the focal unit being measured — typically a person, but sometimes another entity (e.g., a word in a lexical task). | ID |
item | IRW standard Item identifier. | made in the build script |
resp | IRW standard Response value. | made in the build script |
| Respondent covariates | ||
cov_accidents | Covariate | accident |
cov_age | Covariate | age |
cov_drives_with_friends | Covariate | friends |
cov_driving_freq | Covariate | Frequency |
cov_driving_years | Covariate | Experience |
cov_education | Covariate | education |
cov_penalties | Covariate | penalty |
cov_sex | Covariate | sex |
What item codes and covariate values stand for is in the codebook released with the source data.
Or load it directly in R or Python (both need a free Redivis account; the first call opens a browser to sign in):
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("li_2025_risky_driving")
# Python
pip install irw
import irw
df = irw.fetch("li_2025_risky_driving")
@article{Li2025,
author = {Li, W. and Liu, J. and Wang, Y. and Sun, L.},
year = {2025},
title = {Psychometric adaptation and validity of the {R}esistance to {P}eer {I}nfluence {S}cale among young {C}hinese drivers and its links with peer pressure and risky driving behaviours},
journal = {Behavioral Sciences},
volume = {15},
number = {9},
pages = {1237},
doi = {10.6084/m9.figshare.29815862}
}
| IRW version | v584 |
|---|---|
| Redivis dataset | item_response_warehouse_6 v5.11 |
| Redivis dataset DOI | 10.57761/qahq-j855 |
| Manifest pin for this IRW version | v5.11 |
| Metadata source | irw_meta v44.0 |